Parse PRD files, URLs, or text into structured requirements artifacts.
npx skills add https://github.com/hamzaPixl/pixl-ai --skill prd-analysis
Please help me install this Agent Skill. Skill: prd-analysis Source: https://github.com/hamzaPixl/pixl-ai/tree/main/packages/crew/skills/prd-analysis Command: npx skills add https://github.com/hamzaPixl/pixl-ai --skill prd-analysis
Converts unstructured product requirements documents (files, URLs, or pasted text) into a standardized, machine-readable project foundation so downstream planning and review workflows can run reliably without manual reformatting.
Analyze the provided PRD and write structured artifacts to .context/spec/requirements.json and .context/project-overview.md.
High-intent search queries and answers about installing and using this skill.
You can analyze a product requirements document by ingesting files, URLs, or pasted text to generate a structured JSON artifact containing atomic requirements with R-IDs, MoSCoW priorities, and acceptance criteria for downstream task planning.
Parsing PRD text into categorized project artifacts involves extracting content into eight predefined categories: overview, domain model, architecture, milestones, features, technical requirements, risks, and open questions, then persisting the results as machine-readable files.
Yes, you can use a markdown PRD file as input to generate a project-overview markdown file alongside a requirements JSON that includes MoSCoW priorities and acceptance criteria for each decomposed atomic requirement.
When decomposing a spec for engineering teams, requirements are prioritized using the MoSCoW method, assigning each atomic requirement an R-ID and specific acceptance criteria to ensure structured downstream planning.
Yes, PRD analysis works with unstructured text pasted directly into the prompt, saving the canonical source to a markdown file before parsing it into structured categories and atomic requirements.
When ingesting product requirements from external URLs, the tool relies on explicit extraction and marked inferences to parse content into eight categories, meaning highly ambiguous or unstructured web pages may require additional clarification prompts to ensure accurate decomposition.
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